Mr. Bipul Chandra Biswas | Renewable Energy System | Best Researcher Award

Published on by Global Mechanics Awards

Mr. Bipul Chandra Biswas | Renewable Energy System | Best Researcher Award

Student | Gopalganj Science and Technology University | Bangladesh

B.C. Biswas is an emerging researcher in electrical and electronic engineering with a core focus on power-system optimization, photovoltaic device simulation, and next-generation perovskite solar-cell technologies, combining expertise in circuit analysis, power distribution, energy-system design, and computational modelling; he earned his B.Sc. in Electrical and Electronic Engineering from Gopalganj Science and Technology University (GSTU) with academic distinction, ranking second in his department and receiving the Vice-Chancellor’s Award for academic excellence as well as the Young Researcher Award at ABCD Laboratory, where he served as Junior Research Collaborator in the Energy and Technology Research Division (ETRD) and contributed to investigations in renewable-energy integration and sustainable power-conversion strategies, developing solid skills in SCAPS-1D photovoltaic simulation, density-functional-theory-based material analysis, and machine-learning-driven optoelectronic optimization for lead-free perovskite absorbers such as Ca₃BiCl₃, Ca₃BiI₃, Sr₃PF₃, Ca₃NBr₃, Mg₃BiCl₃, Ca₃BiF₃, and Ca₃BiBr₃, authoring and co-authoring a series of peer-reviewed publications in journals including Journal of Computational Chemistry, Physica B Condensed Matter, Solar Energy Materials and Solar Cells, and Materials Science and Engineering B, where his research highlighted comprehensive optoelectronic property analysis, charge-transport-layer engineering, bifacial cell performance improvement, and machine-learning-guided HTL selection for enhanced open-circuit voltage and efficiency gains; his undergraduate thesis on perovskite-solar-cell performance optimization under the guidance of Dr A.T.M. Saiful Islam is under journal review, and he has several additional manuscripts on transport-layer tuning and advanced ML-assisted device modelling currently under peer-review, reflecting a strong trajectory of scholarly productivity at the entry level.

Profile: Google Scholar

Featured Publications:

Shimul, A. I., Biswas, B. C., Ghosh, A., Alrafai, H. A., & Hassan, A. A. (2025). A study on optoelectronic properties and charge transport layer influence in novel Sr₃PF₃-based perovskite solar cells using numerical simulation and machine learning. Solar Energy Materials and Solar Cells, 293, 113838.

Shimul, A. I., Biswas, B. C., Ghosh, A., Awwad, N. S., & Chaudhry, A. R. (2025). Performance assessment and machine-learning-driven optimization of Ca₃NBr₃-based bifacial perovskite solar cells: Improving VOC via HTL and charge-transport-layer analysis. Materials Science and Engineering: B, 322, 118600.

Biswas, B. C., Shimul, A. I., Ghosh, A., Awaad, N. S., & Ibrahium, H. A. (2025). Exploring lead-free Ca₃BiCl₃-based perovskite solar cells: A computational comparison of charge-transport layers with DFT and SCAPS-1D. Journal of Computational Chemistry, 46(25), e70231.

Biswas, B. C., Shimul, A. I., Alshihri, A. A., El-Rayyes, A., Khan, M. T., & Rahman, M. A. (2025). Design and optimization of Ca₃BiI₃-based solar cells through a comprehensive analysis of optoelectronic properties and charge-transport layers using simulation and ML. Physica B: Condensed Matter, 417770.

Anish Kumar J | Electrical | Best Researcher Award

Published on by Global Mechanics Awards

Dr. Anish Kumar J | Electrical | Best Researcher Award

Associate Professor | Saveetha Engineering College | India

Dr. Anish Kumar J is an accomplished academic and researcher in Electrical and Electronics Engineering with nearly two decades of teaching, research, and project supervision experience. Currently serving as an Associate Professor at Saveetha Engineering College, he has guided six Ph.D. scholars under Anna University and contributed significantly to advancements in machine learning, signal processing, and electrical systems. His academic journey spans a B.E. in Electrical and Electronics Engineering, an M.E. in Applied Electronics, and a Ph.D. in Information and Communication Engineering from Anna University. Dr. Anish Kumar J has worked on government-funded projects, including collaborations with NVIDIA, focusing on integrating machine learning and deep learning into IoT systems. His Ph.D. research emphasized predictive modeling of induction motor performance using multimodal sensor signals and machine learning approaches. With a strong record in teaching, mentoring, and applied research, he continues to contribute to both academia and industry through impactful projects and innovation.

Professional Profile

Google Scholar

Education

Dr. Anish Kumar J pursued his academic career with consistent excellence across engineering and applied research. He completed his schooling at L.M.S. Higher Secondary School, Palliyadi, securing SSLC under the Tamil Nadu State Board of Secondary Education. He obtained his B.E. degree in Electrical and Electronics Engineering from C.S.I. Institute of Technology, Manonmaniam Sundaranar University, in Building on this foundation, he pursued an M.E. in Applied Electronics at PSNA College of Engineering & Technology, Anna University, graduating. His postgraduate research involved enhancing exemplar algorithms with image processing techniques for object removal, he earned his Ph.D. in Information and Communication Engineering from RMK Engineering College, Anna University. His doctoral thesis focused on predicting rotor slot size variations in induction motors using multimodal sensor signals and machine learning methods, applying MATLAB and wavelet transform techniques to advance predictive maintenance in electrical machines.

Experience

Dr. Anish Kumar J has an extensive teaching and research career spanning  He began as a Lecturer in ECE at The Rajaas Engineering College, followed by S.S.M. Engineering College and LCR College of Engineering & Technology, he has served as Associate Professor in the School of Computing and Technology (SCOFT) at Saveetha Engineering College. Over these years, he has guided six Ph.D. scholars under Anna University and contributed to curriculum development, research supervision, and collaborative projects. He has coordinated funded projects, including a notable NVIDIA-supported grant on integrating machine learning and deep learning in IoT systems. His teaching expertise spans electrical systems, machine learning applications, and applied electronics, while his research extends to predictive modeling, IoT, and smart energy systems. His career demonstrates a balance between academic leadership, research innovation, and mentoring the next generation of engineers and scientists.

Awards and Honors

Dr. Anish Kumar J has earned recognition for his academic excellence, research contributions, and leadership in engineering education. He successfully secured a government-funded project in collaboration with NVIDIA, titled Integrating Machine Learning and Deep Learning in Real-time IoT Systems, with a grant. His Ph.D. thesis work on induction motor fault prediction using multimodal sensor signals and machine learning was acknowledged as an innovative contribution to predictive maintenance and smart electrical systems. Additionally, he received approval for ATAL FDP proposals under the AICTE scheme for the reflecting his strong engagement in faculty development and capacity-building initiatives. His continuous role as a supervisor for six Ph.D. scholars at Anna University further demonstrates the trust and recognition he has earned in the academic community. While his achievements highlight research and academic leadership, ongoing engagement with international collaborations and high-impact publications will further enhance his honors portfolio.

Research Focus

Dr. Anish Kumar J focuses on interdisciplinary research in machine learning, signal processing, and electrical engineering applications. His Ph.D. work centered on predicting rotor slot size variations in induction motors using multimodal sensor signals and machine learning models, integrating wavelet transforms and MATLAB-based algorithms. His broader research interests include electrical machine diagnostics, IoT-enabled smart systems, deep learning integration, and predictive maintenance. A key area of his work is applying AI and ML models to improve fault detection, enhance system efficiency, and develop intelligent industrial applications. He also explores algorithmic enhancements in image processing, with applications ranging from object recognition to optimization of real-time systems. Through funded projects, such as the NVIDIA-supported IoT initiative, he has expanded his research to practical, real-time contexts. His focus on bridging traditional electrical engineering with modern computational techniques reflects his commitment to advancing next-generation smart technologies and sustainable engineering solutions.

Publication Top Notes 

A Comprehensive Review and Analysis of the Allocation of Electric Vehicle Charging Stations in Distribution Networks
Cited By; 143
Year; 2024

Induction motor rotor slot variation measurement using logistic regression
Charging Stations in Distribution Networks
Cited By; 22
Year; 2022

Conclusion

The candidate’s extensive research experience, innovative research projects, and leadership in guiding Ph.D. scholars make them a strong contender for the Best Researcher Award. With further development of their publication record, interdisciplinary collaborations, and global reach, they could solidify their position as a leading researcher in their field.

Yunfeng Wen | Power systems plannning and operation | Best Researcher Award

Published on by Global Mechanics Awards

Prof. Yunfeng Wen | Power systems plannning and operation | Best Researcher Award

Professor,Hunan University, China

Yifan Wen is a Professor at the National Power Conversion and Control Engineering Technology Research Center, College of Electrical and Information Engineering, Hunan University. His research focuses on power systems, renewable energy integration, and energy internet. He has published numerous papers and serves as an associate editor for several IEEE and IET journals.

Profile

scopus

Education 🎓

B.S. in Electrical Engineering, Sichuan University, China (2010) Ph.D. in Electrical Engineering, Zhejiang University, China (2015)

Experience 🧪

Lecturer, Chongqing University, China (2015-2018)  Associate Professor, Hunan University, China (2018-2022) Professor, Hunan University, China (2023-present)  Post-Doctoral Research Fellow, University of Saskatchewan, Canada (2016-2017)  Visiting Scholar, University of Washington, USA (2012-2013

Awards & Honors �

Unfortunately, the provided text does not mention specific awards or honors received by Yifan Wen.

Research Focus 🔍

Power Systems Planning and Operation: Investigating the planning and operation of power systems with high penetration of renewable energy sources.  Grid Integration of Renewables and Storages: Developing strategies for integrating renewable energy sources and energy storage systems into the grid. Artificial Intelligence and Data Analytics for Energy Internet: Applying artificial intelligence and data analytics techniques to optimize energy internet operations.  Stability Analysis and Control of Low-Inertia Grids: Investigating the stability analysis and control of low-inertia grids with high penetration of renewable energy sources.

Publications📚

1. An Iteration-Based Minimum Inertia Requirement Assessment Method Considering Frequency Security Constraints 💡
2. Inertia Security Evaluation and Application in Low-Inertia Power Systems 🔋
3. Total Transfer Capacity Evaluation of HVDC Tie-lines Under Frequency Security Constraints 💻
4. Coordinated Planning Method for New Energy Station Siting and Network Considering Short Circuit Ratio Constraints 📈
5. Emergency Frequency Control Strategy for Double-high Sending-end Grids With Coordination of Multiple Resources 🚨
6. Operating Reserve Capacity Allocation Strategy and Optimization Model with Coordinated Participation of Source-Network-Load-Storage 📊
7. Estimation of Medium- and Long-term Inertia Level Tendency for Power System and Its Application 🔍
8. Short-circuit Current Suppression Strategy for Receiving-end Power Grid Based on Coordination of Current Limiter Configuration and Network Structure Optimization 🔌
9. Inertia Requirement of Power System: Concepts, Indexes, and Evaluation Method 📝
10. Review on the New Energy Accommodation Capability Evaluation Methods Considering Multi-dimensional Factors 📊

Conclusion 🏆

Yifan Wen’s impressive academic and research experience, interdisciplinary research approach, academic affiliations, awards and honors, and research output make him a strong candidate for the Best Researcher Award. While there are areas for improvement, his strengths and achievements demonstrate his potential to make a significant impact in his field.

Haoting Li | Geoenergy | Best Researcher Award

Published on by Global Mechanics Awards

Dr. Haoting Li | Geoenergy | Best Researcher Award

Dr,Shenyang University of Chemical Technology, China

Dr. Haoting Li is a Lecturer at Shenyang University of Chemical Technology, specializing in petroleum engineering, multiphase flow, and porous media research. He earned his Doctor of Engineering from Northeast Petroleum University in 2022 and was a visiting student researcher at the Korea Advanced Institute of Science and Technology. His research focuses on particle-fluid interactions, solid-liquid behavior, and advanced heat transfer mechanisms. Dr. Li has published extensively in top-tier journals, contributing to the fields of energy engineering, fluid mechanics, and sustainable technologies. He has led multiple research projects funded by Liaoning Province and has received prestigious awards, including the Outstanding Paper Award for Young Scholars and the China Petroleum Science Top Ten Paper Award. With a strong background in computational fluid dynamics and experimental analysis, he continues to make significant advancements in petroleum engineering and environmental technologies.

Profile

scopus

Education 🎓

Doctor of Engineering (2019-2022) – Northeast Petroleum University, specializing in Oil and Gas Engineering. Visiting Student Researcher (2021-2022) – Korea Advanced Institute of Science and Technology, focusing on Civil and Environmental Engineering. Master of Engineering (2016-2019) – Northeast Petroleum University, majoring in Oil and Gas Storage and Transportation. Bachelor of Engineering (2012-2016) – Northeast Petroleum University, with a specialization in Oil and Gas Storage and Transportation. Dr. Li’s academic journey reflects a strong foundation in petroleum and energy engineering. His doctoral research emphasized particle multiphase flow in porous media, while his international exposure at KAIST broadened his expertise in advanced fluid mechanics and environmental engineering applications. His research contributions integrate theoretical analysis and computational simulations for enhancing energy efficiency in petroleum processes.

Professional Experience 💼

Lecturer (2023 – Present) – Shenyang University of Chemical Technology, School of Mechanical and Power Engineering. Conducts research on particle multiphase flow, heat transfer, and porous media applications. Guides students in advanced computational simulations using CFD-DEM methodologies. Research Engineer (2021-2022) – Korea Advanced Institute of Science and Technology. Investigated solid-liquid interactions in environmental and petroleum applications. Developed novel simulation models for multiphase fluid flow and energy efficiency. Researcher (2019-2022) – Northeast Petroleum University. Focused on complex fluid flow behavior in petroleum reservoirs. Published high-impact papers in fluid mechanics and energy engineering.

Awards and Honors 🏅

Outstanding Paper Award of Young Scholar Chen Xuejun (2021) 🏆 – Recognized by the Multiphase Flow Special Committee of the Chinese Society of Engineering Thermophysics for exceptional research in multiphase flow modeling. China Petroleum Science Top Ten Paper Award (2020) 🏅 – Awarded by the China Petroleum and Chemical Industry Federation for significant contributions to petroleum science. Liaoning Province Research Grants (2023 & 2025) 💰 – Principal investigator for funded projects on particle multiphase flow and green energy applications. Best Research Presentation Award 🎤 – Recognized at international conferences for pioneering research in porous media and petroleum engineering.

Research Focus 🔬

Particle Multiphase Flow in Petroleum Engineering – Investigating the migration and interaction of solid particles in porous reservoirs. Solid-Liquid Interaction – Developing CFD-DEM models to analyze fluid-driven particle movement. Complex Fluid Flow & Heat Transfer – Studying fluid dynamics and heat exchange in porous media for energy efficiency. New Energy and Environmental Technologies – Exploring green extraction methods and renewable energy applications in petroleum engineering.

Publications

Simulation on detachment and migration behaviors of mineral particles induced by fluid flow in porous media based on CFD-DEM – Geoenergy Science and Engineering, 2025

Mechanism analysis and energy-saving strengthening process of separating alcohol-containing azeotrope by green mixed solvent extraction distillation – Journal of Molecular Liquids, 2025

Prediction of hydrodynamics in a liquid–solid fluidized bed using the densimetric Froude number-based drag model – Chemical Engineering Science, 2025

CFD-DEM simulation of aggregation and growth behaviors of fluid-flow-driven migrating particles in porous media – Geoenergy Science and Engineering, 2023

Flow behaviors of ellipsoidal suspended particles in porous reservoir rocks using CFD-DEM combined with multi-element particle model – Granular Matter, 2022

Simulation on flow behavior of particles and its effect on heat transfer in porous media – Journal of Petroleum Science and Engineering, 2021

Conclusion

Haoting Li is an exceptional candidate for the Best Researcher Award, given his strong academic credentials, high-impact research, and recognition in petroleum engineering and multiphase flow studies. His work advances critical energy solutions, and with continued expansion into leadership roles, industrial collaboration, and renewable energy research, he can establish himself as a global thought leader.